Wealth Management and Financial Data Science: a short guide

July 1, 2018

Data Science is everywhere. Data is the fuel of the digital economy. There has been an explosion in the velocity, variety and volume of data of all kinds: social media activity, mobile interactions, real-time market feeds, customer service records, transaction details, information from existing databases – there’s no end to this tidal wave.

Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

OTHER WHITEPAPERS
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Big Data Analysis with Revolution R Enterprise

whitePaper | August 10, 2010

The R language is well established as the language for doing statistics, data analysis, data-mining algorithm development, stock trading, credit risk scoring, market basket analysis and all manner of predictive analytics. However, given the deluge of data that must be processed and analyzed today, many organizations have been reticent about deploying R beyond research into production applications. The main barrier is that R is a memory-bound language. All data used in calculations — vectors, matrices, lists, data frames, and so forth — all need to be held in memory. Even for modern computers with 64-bit address spaces and huge amounts of RAM, dealing with data sets that are tens of gigabytes and hundreds of millions of rows (or larger) can present a significant challenge. The problem isn’t just one of capacity, that is, being simply being able to accommodate the data in memory for analysis. For mission-critical applications, performance is also a prime consideration: if the overnight analysis does not complete in time for the open of business the next day, that’s just as much of a failure as an out-of-memory error. And with data set sizes growing rapidly, scalability is also of concern: even if the in-memory analysis completes today, the IT manager still needs the confidence that the production run will complete — on time! — as the data set grows.

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Unleash digital intelligence with data and apps

whitePaper | May 9, 2018

In a world of rapid market change, technological upheaval and massive restructuring, arguably, your most important business asset isn’t your products, technologies, or processes — it’s your data. The ability to transform your data into digital intelligence is central to competitive advantage. Only then can it fuel and automate processes, accelerate decisions, bring unique client experiences to life, and ultimately, disrupt entire industries. The problem is that data often remains trapped in siloed data stores or applications — both on premises, and increasingly, in the cloud. Different vendor APIs, architectures and data formats can make it hard to access and apply the advanced analytics needed to elevate data’s value — and make it available to the right people. What’s needed is a more proactive approach that integrates data and applications in all its forms, on and off premises, and provides greater visibility and control. The right solution must also secure and govern all types of data, from any source, across a hybrid cloud infrastructure.

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Creating real value from the data life cycle

whitePaper |

The big impact of Big Data in the post-modern world is unquestionable, un-ignorable and unstoppable today. While there are certain discussions around Big Data being really big, here to stay or just an over hyped fad; there are facts as shared in the following sections of this whitepaper that validate one thing - there is no knowing of the limits and dimensions that data in the digital world can assume. As of now, there are only predictions, forecasts that form the basis for businesses to decide their own course of action by taking advantage of this new window of opportunity with high-end intricate technology based resources and tools. These are nothing but ways and means to harness the mammoth and draw necessary inferences for making smart, intelligent business decisions.

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IoT Big Data Common Enablers for Analytics Services Version 1.0

whitePaper | December 20, 2017

"Analytics Services" are increasingly being offered by Mobile Network Operators to accompany traditional services such as voice, mobile messaging and connectivity. A good example of such a service would be the processing of mobile network data to produce a population statistics report which is used for transportation planning. While there are formal technical specifications defined for core mobile network services this is not the case for "Analytics Services".

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Data Science: Salary Report

whitePaper |

The 21st century’s most sought-after job offers tremendous scope for professionals looking to make it big. And more importantly, certified Data Science professionals make the big bucks. But how much can you really expect to make? This salary report that surveys the salaries of Data Science professionals from across the world was compiled with exactly this end in mind.

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How to Make Real-Time Business Intelligence Work on Hadoop

whitePaper |

This white paper explains how index-access architecture combined with adaptive caching can help you achieve truly interactive response times for BI on big data, and how the underlying technology works.It analyzes the challenges of implementing indexes for big data and how Jethro solved these challenges. It then discusses how the Jethro design of separating compute from storage works with Hadoop and with Amazon S3.

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Spotlight

Pivotal

Pivotal’s cloud native platform drives software innovation for many of the world’s most admired brands. With millions of developers in communities around the world, Pivotal technology touches billions of users every day. After shaping the software development culture of Silicon Valley's most valuable companies for over a decade, today Pivotal leads a global technology movement transforming how the world builds software.

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